DocumentCode
3390894
Title
A self-organizing map and its modeling for discovering malignant network traffic
Author
Langin, Chet ; Zhou, Hongbo ; Rahimi, Shahram ; Gupta, Bidyut ; Zargham, Mehdi ; Sayeh, Mohammad R.
Author_Institution
Dept. of Comput. Sci., Southern Illinois Univ., Carbondale, IL
fYear
2009
fDate
March 30 2009-April 2 2009
Firstpage
122
Lastpage
129
Abstract
Model-based intrusion detection and knowledge discovery are combined to cluster and classify P2P botnet traffic and other malignant network activity by using a self-organizing map (som) self-trained on denied Internet firewall log entries. The SOM analyzed new firewall log entries in a case study to classify similar network activity, and discovered previously unknown local P2P bot traffic and other security issues.
Keywords
Internet; data mining; peer-to-peer computing; security of data; telecommunication traffic; P2P botnet traffic; denied Internet firewall log entries; knowledge discovery; malignant network traffic; model-based intrusion detection; self-organizing map; Cancer; Cryptography; Internet; Intrusion detection; Military computing; Peer to peer computing; Protocols; Relays; Telecommunication traffic; Traffic control;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence in Cyber Security, 2009. CICS '09. IEEE Symposium on
Conference_Location
Nashville, TN
Print_ISBN
978-1-4244-2769-7
Type
conf
DOI
10.1109/CICYBS.2009.4925099
Filename
4925099
Link To Document